Classifying NSFW Images; Shocking & Disturbing

Peter Prestipino

Posted on 10.03.2016

The team behind Yahoo's system to mark NSFW (not suitable for work) content on the 'Net has just made the technology open source.

The NSFW problem has captivated (pun intended) researchers and developers for decades, and with the evolution of computer vision, improved training data and deep learning algorithms, computers are now able to automatically classify NSFW image content with far greater precision.

Defining what is classified as NSFW is subjective, of course, and can prove quite complex. Yahoo's convolutional neural network, however, brings a great deal of sophistication to the problem in pursuit of an answer.

In machine learning, according to Wikipedia, a convolutional neural network (CNN, or ConvNet) is a type of feed-forward artificial neural network in which the connectivity pattern between its neurons is inspired by the organization of the animal visual cortex.

Yahoo's technology essentially combs through a vast variety of imagery and gives each a score, from 0 to 1, on how NSFW it thinks that particular picture is. This could be useful in many situations, and not just censorship. Such a system, for example, could inspect emails and messages without any human intervention and provide a warning if an image is potentially NSFW.

Speak out! How do you ensure that your own users aren't exposed to NSFW content as they interact with your website and mobile applications?